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About H5 H5 is the leading provider of information retrieval and document analysis services for Fortune 500 corporate legal departments and leading law firms. H5 was recognized with a number three ranking among the fastest growing technology companies by Deloitte's Technology Fast 50 Program. H5, a privately held company with strong venture capitalist backing, was also included in the "Cool Vendors in Content Management, 2007" report by premier analyst firm, Gartner, Inc.

H5 is an information retrieval firm that helps law firms and corporations search, assess, and manage electronically stored information. Through a full range of advisory, document review, and litigation support services, H5 finds the information clients need for litigation and investigations, compliance, and litigation readiness. Our approach - which combines advanced technologies with expertise in law, linguistics, computer science, and statistics - consistently reduces clients' information management costs while minimizing their risk.

Employment opportunities with H5 are differentiated by our unique value proposition. We offer an environment where you will partner with a diverse team of sophisticated knowledge workers who share a drive to succeed, a passion for solving our clients' most challenging problems and a strong intellectual curiosity. Our expectations for performance are high and each team member has a clear line of sight connecting their individual contributions toward the achievement of department and corporate objectives. For more information please visit the website listed above.

Overview: In this position, you will draw on your familiarity with machine learning techniques and experience with their application to create classification systems extending and refining H5's industry-leading approach to legal document review.

Responsibilities: - Develop a classifier-based approach to high-quality, human-computer information retrieval - Become familiar with the characteristics of the legal document review problem and with H5's existing approach - Collaborate with internal experts to determine feature requirements and parameters of an acceptable document review solution - Acquire, create or direct the creation of data resources needed for development and/or evaluation - Perform experiments and implement and test prototype systems as necessary, sharing results with other researchers and end-users, in order to arrive at a functioning approach acceptable to users - Perform a convincing large-scale evaluation of the document review solution in the context of a real- or near-real scale project - Create instrumentation in order to monitor evaluation process; collect, synthesize and report on data in order to assess effectiveness of the solution under evaluation - Work closely with users to set expectations and communicate differences with existing solution and benefits of the new approach

Requirements: - Proven ability to develop efficient software - Master's or PhD degree or equivalent experience in machine learning or closely related field - Knowledge of machine learning research and literature - Hands-on experience with techniques such as Support Vector Machines (SVM), Decision Trees and Logistic Regression - Track record of effective application of machine learning approaches in real-world applications